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Welcome to My GitHub. πŸ‘‹

I'm YoungDon Choi, a principal researcher at K-water AI research Lab ( https://github.com/Kwater-AILab) . I have worked at K-water (https://www.kwater.or.kr/eng/about/sub02/kwaterPage.do?s_mid=1099) since 2003 with many experiences such as dam operation, water resources survey and planning, water technology strategy, and water information system. Currently, I'm working at K-water AI research Lab to apply AI in water resources fields.

I did my PhD from 2017 to 2021 at the UVA Hydroinformatics research group (https://uvahydroinformatics.org/team/) in University of Virginia (https://www.virginia.edu/). This is my Dissertation (https://doi.org/10.18130/g9tg-0c69), google scholar(https://scholar.google.com/citations?user=VCyCE5QAAAAJ&hl=en) and Resume(https://github.com/DavidChoi76/profile/blob/main/YD_Choi_17June2022.pdf)

These are my current research. πŸ€“ Focusing πŸ€”

  1. πŸ”­ Application of neuralhydrology and other AI technologies for upstream and downstream analysis for dam operation
  1. 🌱 Long-Term Water Demand Forecasting

  2. πŸ‘― Satellite Rainfall Distribution using Machine Learning

  3. πŸ”­ Urban Inundation Forecasting using Machine Learning as Surrogate Model

  4. 🌱 Application of NeRF and 3DGS in Water Infrastructures

  5. πŸ‘― Drought Quantification using Social data such as Newspapers

Study for Deeper Understanding. πŸ€“ Focusing πŸ€”

  1. Differentiable Modeling

Study HydroMT. πŸ€“ Focusing πŸ€”

  1. hydromt: https://github.com/DavidChoi76/hydromt
  2. hydromt_wflow: https://github.com/DavidChoi76/hydromt_wflow
  3. hydromt_delwaq: https://github.com/DavidChoi76/hydromt_delwaq
  4. hydromt_sfincs: https://github.com/DavidChoi76/hydromt_sfincs
  5. hydromt_fiat: https://github.com/DavidChoi76/hydromt_fiat
  6. hydromt_delft3dfm: https://github.com/DavidChoi76/hydromt_delft3dfm

YoungDon Choi's Projects

.github icon .github

Community health files for the @GitHub organization

30days icon 30days

#30DaysOfStreamlit is a 30-day social challenge for you to build and deploy Streamlit apps.

advancedml icon advancedml

Reading list for the Advanced Machine Learning Course

ai-as-a-service icon ai-as-a-service

γ€Žμ‰½κ²Œ λ°°μš°λŠ” AWS AI μ„œλΉ„μŠ€γ€(2022, ν•œλΉ›λ―Έλ””μ–΄)의 μ˜ˆμ‹œ μ½”λ“œ μ €μž₯μ†Œμž…λ‹ˆλ‹€.

altair icon altair

Declarative statistical visualization library for Python

amalia-lite icon amalia-lite

Modular application framework for network analysis and simulation

ams-ml-python-course icon ams-ml-python-course

Machine Learning in Python for Environmental Science Problems AMS Short Course Material

atlantis icon atlantis

A Benchmark for Semantic Segmentation of Waterbody Images

autovideo icon autovideo

AutoVideo: An Automated Video Action Recognition System

awesome-dataviz icon awesome-dataviz

:chart_with_upwards_trend: A curated list of awesome data visualization libraries and resources.

awesome-earthobservation-code icon awesome-earthobservation-code

A curated list of awesome tools, tutorials, code, helpful projects, links, stuff about Earth Observation and Geospatial stuff!

awesome-jupyter icon awesome-jupyter

A curated list of awesome Jupyter projects, libraries and resources

awesome-nerf icon awesome-nerf

A curated list of awesome neural radiance fields papers

camels icon camels

Python interface to the CAMELS dataset.

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